Top Senior Machine Learning Jobs in Pensacola, FL

Develop AI agents, chatbots, and machine learning models for a modernized federal data science platform. Research and standardize AI capabilities in Databricks and Palantir, prompt-engineer LLMs, integrate AI into DevOps pipelines, and train models on production datasets for prediction and anomaly detection. The role requires collaboration with developers and customers, database familiarity, Agile experience, documentation, and an active or obtainable DoD Secret clearance.

Lead computational platform development for biological design, optimization, and functional prediction. Collaborate with wet-lab scientists to validate predictions, oversee data infrastructure and computational workflows, and contribute to technology roadmaps, funding proposals, and partnerships. The role requires developing machine learning methods for biological sequence and structure analysis, translating biological problems into computational solutions, and leading technical teams across computational and experimental disciplines.

Build and deploy machine learning models that personalize insurance products, analyze product data, design experiments, and measure model impact. The role owns the full data science lifecycle, including data wrangling, production coding, model monitoring, retraining, and experimentation. Responsibilities also include cross-functional collaboration, code reviews, mentoring data scientists, and improving platform practices.

Leads client-facing manufacturing and automotive analytics, data, AI, and digital transformation engagements. Responsibilities include executive stakeholder management, consulting, solution design, account growth, proposal development, commercial oversight, program governance, delivery leadership, and capability building. The role develops transformation roadmaps, modernizes data platforms, guides AI and analytics use cases, manages strategic portfolios up to $10M–$15M annually, and mentors multidisciplinary teams.

Lead the development, optimization, and production deployment of advanced machine learning algorithms for advertising effectiveness and ROI. Build scalable ML models, write efficient code, collaborate with machine learning engineers, prototype and test algorithms and data pipelines, and drive iterative improvements using historical data and rigorous performance analysis.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Lead research into novel AI architectures, learning algorithms, reasoning, knowledge representation, and evaluation methodologies. Define and execute ambitious research programs, design experiments, develop large-scale content evaluation systems, mentor research engineers, and communicate findings through technical publications. The role combines scientific leadership with hands-on innovation focused on language models, factuality, evidence quality, source reliability, and trustworthy AI systems.

Conduct advanced research spanning RF communications, digital signal processing, compressive sensing, machine learning, and resilient network systems. Develop and deploy ML pipelines for RF and time-series data using modern frameworks and MLOps practices. Lead projects from concept through demonstration, publish technical findings, and communicate results to stakeholders. Work may support 5G, non-terrestrial networks, cybersecurity, electronic warfare, SIGINT, radar, and other national security applications.

Leads enterprise field intelligence and portfolio prioritization across pharmaceutical therapeutic areas. Owns targeting, Next Best Action, field orchestration, roadmap governance, capability development, standards, and operating-model transformation. The role aligns cross-functional teams, drives scalable data- and AI-enabled solutions, improves customer engagement, and supports strategic decision-making across field teams and channels.

Lead the strategy, roadmap, and execution of an AI-driven B2B SaaS platform for government contracting. Translate RFP and customer needs into prioritized product enhancements, collaborate with AI research and cross-functional teams, apply agile methodologies using Jira, and drive successful product launches and adoption.

Lead technical pre-sales for large Oil, Gas & Energy accounts, define and implement Databricks-based data and ML/AI strategies, build technical champions, mentor teammates, and drive enterprise adoption through technical leadership and value selling.

Own G2’s research agenda for evaluating AI agents in realistic business workflows. Design benchmarks, task environments, scoring systems, automated and human grading methods, and reliability analyses. Collaborate with engineering and product teams to ship evaluation capabilities, communicate findings to customers and researchers, mentor technical teams, and establish repeatable standards. The role requires hands-on LLM and agent evaluation experience, original research, statistical judgment, product delivery, and technical leadership.

Lead product strategy, roadmap execution, and measurable outcomes for an AI-enabled refinance title decisioning platform. Translate strategy into requirements, user stories, and acceptance criteria; prioritize initiatives against OKRs; and partner with engineering, data science, operations, sales, and marketing. Monitor product health, accuracy, costs, service levels, and performance through metrics and dashboards. Manage stakeholders, customer onboarding, continuous improvement, and automation opportunities across a regulated real estate workflow.

Own and scale Tilt’s credit card acquisition through affiliate partnerships, paid search, and paid social. Lead channel strategy, partner launches, targeting, experimentation, and optimization while collaborating with credit, data science, product, engineering, and marketing. Use SQL and Python to evaluate funnel performance, unit economics, approvals, activation, spend, and credit outcomes. Shape acquisition policies and application experiences to drive profitable growth.

Designs, deploys, and maintains AI and machine learning solutions, including generative AI, LLM, RAG, and conversational AI applications. Owns agentic engineering infrastructure, application guardrails for patient-care workflows, data pipelines, analytics, model governance, monitoring, and cloud deployment. Provides architectural leadership, improves engineering throughput, ensures privacy and compliance, and translates business needs into scalable AI solutions.

Lead product positioning, go-to-market strategy, launches, customer insights, competitive intelligence, messaging, sales enablement, and thought leadership for AI-driven cybersecurity and authentication products. Translate complex AI and machine learning technologies for technical and business audiences, manage marketing plans and budgets, support customer case studies, and mentor a high-performing product marketing team. Partner closely with Product, Engineering, Sales, Marketing, and executive leadership.

Coordinates strategic AI programs across engineering, product, legal, risk, compliance, security, HR, and business teams. Develops execution plans, governance frameworks, status reporting, risk registers, and executive communications. Supports AI platform and agent deployment initiatives, AI policy development, enterprise training, stakeholder alignment, and adoption. Requires strong program management, AI technology understanding, organizational skills, and experience managing complex cross-functional initiatives.

Build and own production-grade generative AI applications for legal technology, specializing in RAG, agentic systems, advanced search, embeddings, reranking, evaluation, and LLM workflows. Responsibilities include architecting modular Python applications, refactoring legacy code, implementing testing and observability, optimizing performance and costs, ensuring resilience and security, reviewing code, and supporting deployments and incident resolution.

Leads the scientific direction and technical roadmap for a permanent magnet research vertical. Responsibilities include guiding computational materials discovery and AI modeling, developing manufacturable magnet formulations, building and mentoring multidisciplinary teams, managing intellectual property, coordinating national laboratory and industry partnerships, and connecting simulation with experimental validation. The role also supports commercial licensing, external scientific communications, publications, and federally funded research programs.

Own the strategy, roadmap, and success metrics for AI security capabilities across the Pathfinder platform. Serve as the internal expert on agentic AI threats, identity security, and emerging attack techniques. Define requirements for securing AI agents, MCP servers, and orchestration frameworks; conduct market and competitive research; lead design partner programs; coordinate cross-portfolio product work; and support analyst, customer, marketing, and pre-sales engagements.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Manages backlogs, roadmaps, prioritization, requirements, user stories, release planning, and product metrics. Partners with stakeholders, Engineering, AI, UX, Data Science, and Architecture teams to deliver enterprise AI-enabled products aligned with governance, Responsible AI, and business objectives.

Own and improve ClickUp’s voice AI systems, including real-time speech-to-text, audio processing, context-aware transcription, LLM post-processing, mention resolution, formatting, and voice-to-action workflows. Evaluate and integrate ASR models for accuracy, latency, and cost, while collaborating across product and platform teams to deliver voice and multimodal assistant features across desktop, mobile, web, and browser extension products.

Leads enterprise CrowdStrike deployments, architecture, compromise assessments, threat hunting, SOC modernization, detection engineering, cyber analytics, Purple Team exercises, and incident response. Advises CISOs and executives, manages cross-functional teams, designs global 24/7 SOCs, and coordinates breach containment and recovery. Requires deep CrowdStrike expertise, cybersecurity leadership, scripting, network and detection engineering, and executive communication skills.

Designs and maintains scalable data models, semantic layers, ETL/ELT workflows, data-quality frameworks, and governed analytics products for commercial operations. Owns data solutions from requirements through deployment, monitoring, documentation, and support. Partners with technical and business stakeholders to deliver trusted reporting, dashboards, scorecards, productivity measurements, and AI-enabled decision support.

Designs, builds, and operates observability and SRE systems that improve IT service visibility, reliability, performance, and resilience. Responsibilities include metrics collection, monitoring, alerting, APM, RUM, synthetic transactions, SLOs, incident response, capacity planning, infrastructure automation, self-healing systems, and production readiness reviews. The role also applies AI-enabled operations, supports on-call rotations, reduces operational toil, and partners with development teams on architecture and chaos testing.